Harnessing Artificial Intelligence for Enhanced Scientific Collaboration: Insights from Students and Educational Implications

Использование искусственного интеллекта для повышения эффективности научного сотрудничества: мнения студентов и образовательные последствия
Małgorzata Gawlik-Kobylińska
2024-10-18

Cohen’s Kappa (intra-coder reliability)academic writing and scientific postersartificial intelligence (AI)scientific collaborationthematic analysis
This study aimed to explore students’ perspectives on integrating artificial intelligence (AI) into scientific collaboration, specifically on writing academic articles and creating scientific posters. The research employed open-ended interviews conducted among 61 civil and military students. Opinions were labelled, coded, and gathered into the following categories: positive impact on collaboration, challenges faced, and educational impact. Among the positives were improving efficiency, enhancing the quality of work, and generating new ideas. The challenges concerned experiencing technical difficulties with AI tools, inconsistency in AI outputs, and AI dependence, which may lead to behaviours on the verge of addiction. Regarding educational impact, students noticed that AI helps improve learning new skills, increases engagement in the task, and enhances critical thinking. As one researcher performed the thematic analyses, Cohen’s Kappa statistic was used to ensure intra-coder reliability. This study highlights the need for further research to optimize the use of AI in scientific collaboration while addressing ethical concerns related to students’ motivations for using AI tools, promoting responsible use, and researching students’ emotions, cognitive processes, and behaviours resulting from their interactions with AI tools. The research provides valuable insights for educators and policymakers to integrate AI effectively into academic practice.
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Students experienced challenges using AI tools, including technical difficulties, inconsistent outputs, and risk of dependence bordering on addictive behaviors.
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Students indicated AI can enhance the quality of work and generate new ideas during collaborative scientific tasks.
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Students observed educational benefits of AI: helping learn new skills, increasing engagement, and enhancing critical thinking.
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Students reported AI positively impacts scientific collaboration by improving efficiency in writing academic articles and creating scientific posters.
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The study identifies needs for further research on optimizing AI use in collaboration, addressing ethical concerns, and investigating students’ emotions, cognition, and behaviors with AI.
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Thematic analysis used Cohen’s Kappa to ensure intra-coder reliability, reflecting methodological attention to coding consistency.

Students (civil and military) discussing integration of artificial intelligence into scientific collaboration for writing academic articles and creating scientific posters

Students' perspectives on the impact of AI integration into scientific collaboration, focusing on effects on collaboration (efficiency, quality, idea generation), challenges (technical issues, inconsistent outputs, dependency/addictive behaviours), and educational impacts (skill learning, engagement, critical thinking)

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2024-10-18
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Małgorzata Gawlik-Kobylińska
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